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DFDF - A Descriptive Approach to Data Standardization Data standardization is fundamentally prescriptive; no information system can solve the data integration problem without enforcing certain rules. But the challenge remains at where the rules should be prescribed. Most existing data standards prescribe the rules over the data itself. Excessive use of such an approach, however, leads to inefficient data representation. The alternative approach is to enforce the conforming rules over the description of the data so that data itself can be encoded in any manner. By developing ontologies for describing the data format and software libraries that can understand the ontology, this descriptive approach to data standardization will provide maximal flexibility in data representation while still ensuring the data interoperability.

Linked Data is a method to publish data on the Web and to interlink data between different data sources. Linked Data can be accessed using Semantic Web browsers, just as traditional Web documents are accessed using HTML browsers. However, instead of following document links between HTML pages, Semantic Web browsers enable surfers to navigate between different data sources by following RDF links. RDF links can also be followed by robots or Semantic Web search engines in order to crawl the Semantic Web. See Linked Data - The Story so far and How to publish Linked Data on the Web for more information about Linked Data.

Uberblic.org is an integration service for data on the web. It acts as a layer between data publishers and data consumers. It consolidates and reconciles information in real time into a central data repository, and provides developer APIs on top. We make this consolidated data repository available to everyone who needs access to integrated web data, ranging from web developers to large enterprises. The consolidation platform imports information from open data sources like Wikipedia, Geonames, Musicbrainz, TheMovieDB, and others, can mirror changes from these original data sources in real time, and can integrate enterprise data sources into private consolidated views.

In order to support data set owners to publish their datasets as Linked Data on the Web, as well as to support data consumers to access and integrate Linked Data from the Web, the LATC project has compiled a library of open source toolkits that cover all stages of the Linked Data publication (modeling, linking, serving) and consumption process (discovery, consolidation, application). By gathering high-quality open source tools in the form of a consistent library, we hope to lower the barriers to publishing Linked Data as well as to interacting with the Web of Data.

The Data Cube vocabulary provides a means to do this using the W3C RDF (Resource Description Framework) standard. The model underpinning the Data Cube vocabulary is compatible with the cube model that underlies SDMX (Statistical Data and Metadata eXchange), an ISO standard for exchanging and sharing statistical data and metadata among organizations. The Data Cube vocabulary is a core foundation which supports extension vocabularies to enable publication of other aspects of statistical data flows or other multi-dimensional data sets.

Linked Data is about using the Web to connect related data that wasn't previously linked, or using the Web to lower the barriers to linking data currently linked using other methods. More specifically, Wikipedia defines Linked Data as "a term used to describe a recommended best practice for exposing, sharing, and connecting pieces of data, information, and knowledge on the Semantic Web using URIs and RDF." This site exists to provide a home for, or pointers to, resources from across the Linked Data community.

"Linked Data is one of the core pillars of the Semantic Web, also known as the Web of Data. The Semantic Web is about making links between datasets that are understandable not only to humans, but also to machines, and Linked Data provides the best practices for making these links possible. In other words, Linked Data is a set of design principles for sharing machine-readable interlinked data on the Web."

Extracting Structured Data from the Common Web Crawl More and more websites have started to embed structured data describing products, people, organizations, places, events into their HTML pages. The Web Data Commons project extracts this data from several billion web pages and provides the extracted data for download. Web Data Commons thus enables you to use the data without needing to crawl the Web yourself.

The Dynamic Linked Data Observatory is a framework to monitor Linked Data over an extended period of time. The core goal of our work is to collect frequent, continuous snapshots of a subset of the Web of Data that is interesting for further study and experimentation, with an aim to capture raw data about the dynamics of Linked Data. The resulting corpora will be made openly and continuously available to the Linked Data research community.

The Dynamic Linked Data Observatory is a framework to monitor Linked Data over an extended period of time. The core goal of our work is to collect frequent, continuous snapshots of a subset of the Web of Data that is interesting for further study and experimentation, with an aim to capture raw data about the dynamics of Linked Data. The resulting corpora will be made openly and continuously available to the Linked Data research community.

This portal is about transparency, open government and innovation. The European Commission Data Portal provides access to open public data from the European Commission. It also provides access to data of other Union institutions, bodies, offices and agencies at their request. The published data can be downloaded by everyone interested to facilitate reuse, linking and the creation of innovative services. Moreover, this Data Portal p

A catalyser for the Web of data Datalift brings raw structured data coming from various formats (relational databases, CSV, XML, ...) to semantic data interlinked on the Web of Data. Datalift is an experimental research project funded by the French national research agency. Its goal is to develop a platform to publish and interlink datasets on the Web of data. Datalift will both publish datasets coming from a network of partners and data providers and propose a set of tools for easing the datasets publication process. A few steps to data heaven The project will provide tools allowing to facilitate each step of the publication process:

A catalyser for the Web of data Datalift brings raw structured data coming from various formats (relational databases, CSV, XML, ...) to semantic data interlinked on the Web of Data. Datalift is an experimental research project funded by the French national research agency. Its goal is to develop a platform to publish and interlink datasets on the Web of data. Datalift will both publish datasets coming from a network of partners and data providers and propose a set of tools for easing the datasets publication process. A few steps to data heaven The project will provide tools allowing to facilitate each step of the publication process:

"In addition to the classic "Web of documents" W3C is helping to build a technology stack to support a "Web of data," the sort of data you find in databases. The ultimate goal of the Web of data is to enable computers to do more useful work and to develop systems that can support trusted interactions over the network. The term "Semantic Web" refers to W3C's vision of the Web of linked data. Semantic Web technologies enable people to create data stores on the Web, build vocabularies, and write rules for handling data. Linked data are empowered by technologies such as RDF, SPARQL, OWL, and SKOS."

In addition to the classic "Web of documents" W3C is helping to build a technology stack to support a "Web of data," the sort of data you find in databases. The ultimate goal of the Web of data is to enable computers to do more useful work and to develop systems that can support trusted interactions over the network. The term "Semantic Web" refers to W3C's vision of the Web of linked data. Semantic Web technologies enable people to create data stores on the Web, build vocabularies, and write rules for handling data. Linked data are empowered by technologies such as RDF, SPARQL, OWL, and SKOS.

"In addition to the classic "Web of documents" W3C is helping to build a technology stack to support a "Web of data," the sort of data you find in databases. The ultimate goal of the Web of data is to enable computers to do more useful work and to develop systems that can support trusted interactions over the network. The term "Semantic Web" refers to W3C's vision of the Web of linked data. Semantic Web technologies enable people to create data stores on the Web, build vocabularies, and write rules for handling data. Linked data are empowered by technologies such as RDF, SPARQL, OWL, and SKOS."

CKAN is the world's leading open-source data portal platform. It is a complete out-of-the-box software solution that makes data accessible - by providing tools to streamline publishing, sharing, finding and using data. CKAN is aimed at data publishers (national and regional governments, companies and organizations) wanting to make their data open and available.

Google Refine is a power tool for cleaning up raw data, making it consistent, linking it to data registries like Freebase, augmenting it with more data from other data sources, transforming it into the required format for other tools to consume, and contributing it back to some data sources like Freebase. Google Refine is not a web service but a desktop app that runs on your own computer, so you can process sensitive data with privacy.

Rapid-I provides software, solutions, and services in the fields of predictive analytics, data mining, and text mining. The company concentrates on automatic intelligent analyses on a large-scale base, i.e. for large amounts of structured data like database systems and unstructured data like texts. The open-source data mining specialist Rapid-I enables other companies to use leading-edge technologies for data mining and business intelligence. The discovery and leverage of unused business intelligence from existing data enables better informed decisions and allows for process optimization.

provides an overview of our attempts to a more visual Data Web. The term Data Web refers to the evolution of a mainly document-centric Web toward a more data-oriented Web. In its narrow sense, the term describes pragmatic approaches of the Semantic Web, such as RDF and Linked Data. In a broader sense, it also includes less formal data structures, such as microformats, microdata, tagging, and folksonomies.